About the role
We are looking for an experienced Generative AI Solutions Architect who can design, build, and scale production-grade LLM-powered, AI-assisted, and machine learning solutions.
Responsibilities
- Architect and deliver production-grade Generative AI and ML systems.
- Build reliable, scalable, and maintainable AI solutions from experimentation to production.
- Design and support practical Generative AI use cases such as LLM-powered applications, AI assistants, RAG, and agentic workflows.
- Translate business and client requirements into practical AI solution architectures.
- Work with Data Scientists, Data Engineers, and Software Engineers to turn prototypes into production-ready systems.
- Guide teams on responsible use of AI tools such as GitHub Copilot, Claude Code, Codex, OpenClaw, and similar platforms.
- Mentor software teams and help them use Generative AI tools effectively in their day-to-day engineering work.
- Define and improve LLMOps and MLOps practices, including deployment, monitoring, evaluation, retraining, and feedback loops.
- Build CI/CD pipelines for AI/ML workflows, including data validation, feature engineering, model validation, prompt evaluation, and drift detection.
Requirements
- Practical experience designing LLM-powered applications such as AI assistants, RAG systems, agentic workflows, or AI-assisted engineering tools.
- Strong knowledge of LLM APIs and/or locally hosted LLMs, including tools such as LM Studio, Ollama, vLLM, Hugging Face, Azure OpenAI, or similar platforms.
- Experience with LangSmith, LangChain, LangGraph, foundation models, RAG, MCP, vector databases, or prompt evaluation.
- Hands-on experience with production ML/AI systems and MLOps or LLMOps practices.
- Experience with orchestration and containerization tools such as Docker, Kubernetes, or similar.
- Hands-on experience with monitoring, evaluation, drift detection, and feedback loops in production environments.
- Experience using tools such as GitHub Copilot, Claude Code, Codex, OpenClaw, or similar tools.
- Ability to review, debug, test, and validate AI-generated code before using it in production.
- Ability to mentor engineers and explain Generative AI concepts in a practical, easy-to-understand way.
- Strong programming skills in Python or similar languages.
- Ability to use cutting edge technologies like AI to efficiently deliver tasks.
Benefits
- Lead cross-functional teams and establish enterprise-wide AI best practices.
- Opportunity to architect mission-critical AI/ML solutions for global clients.
- Very competitive salary and excellent career opportunity in a focused and stable organization.
- Most importantly, a friendly work environment with opportunity to learn from a number of highly skilled mentors.
How to apply
Apply through the employer using the Apply button. Include a current CV and, where relevant, links to your GitHub or portfolio. You will leave DataJobs BD; applications go to the employer's own site or email.